CPC G06F 21/44 (2013.01) [G06F 9/4881 (2013.01); G06F 9/5044 (2013.01); G06F 9/5066 (2013.01); G06F 9/5072 (2013.01); G06F 16/535 (2019.01); G06F 16/538 (2019.01); G06F 16/54 (2019.01); G06F 16/951 (2019.01); G06F 18/21 (2023.01); G06F 18/211 (2023.01); G06F 18/213 (2023.01); G06F 18/2163 (2023.01); G06F 18/22 (2023.01); G06F 18/24 (2023.01); G06F 18/24143 (2023.01); G06F 21/45 (2013.01); G06F 21/53 (2013.01); G06F 21/6254 (2013.01); G06F 21/64 (2013.01); G06K 15/1886 (2013.01); G06N 3/04 (2013.01); G06N 3/045 (2023.01); G06N 3/063 (2013.01); G06N 3/08 (2013.01); G06N 5/022 (2013.01); G06T 7/11 (2017.01); G06T 7/70 (2017.01); G06V 10/20 (2022.01); G06V 10/40 (2022.01); G06V 10/454 (2022.01); G06V 10/75 (2022.01); G06V 10/82 (2022.01); G06V 10/95 (2022.01); G06V 10/96 (2022.01); G06V 20/00 (2022.01); G06V 30/19173 (2022.01); G06V 30/274 (2022.01); G06V 40/161 (2022.01); G06V 40/20 (2022.01); H04L 9/0643 (2013.01); H04L 9/3239 (2013.01); H04L 67/12 (2013.01); H04L 67/51 (2022.05); H04N 19/46 (2014.11); H04N 19/80 (2014.11); H04W 4/70 (2018.02); G06F 18/24323 (2023.01); G06F 2209/503 (2013.01); G06F 2209/506 (2013.01); G06F 2221/2117 (2013.01); G06T 7/20 (2013.01); G06T 7/223 (2017.01); G06T 2207/10016 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20024 (2013.01); G06T 2207/20052 (2013.01); G06T 2207/20056 (2013.01); G06T 2207/20064 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30242 (2013.01); G06V 30/194 (2022.01); G06V 2201/10 (2022.01); H04L 9/50 (2022.05); H04L 67/10 (2013.01); H04N 19/12 (2014.11); H04N 19/124 (2014.11); H04N 19/167 (2014.11); H04N 19/172 (2014.11); H04N 19/176 (2014.11); H04N 19/42 (2014.11); H04N 19/44 (2014.11); H04N 19/48 (2014.11); H04N 19/513 (2014.11); H04N 19/625 (2014.11); H04N 19/63 (2014.11); H04W 12/02 (2013.01)] | 20 Claims |
1. At least one non-transitory computer-readable storage medium having instructions stored thereon, wherein the instructions, when executed on processing circuitry, cause the processing circuitry to:
receive a frequency-domain representation of image data, wherein the frequency-domain representation comprises a plurality of sets of transform coefficients for a plurality of blocks of the image data; and
detect content in the image data using a convolutional neural network (CNN), wherein the CNN is trained to detect the content in the image data based on corresponding transform coefficients among the plurality of blocks.
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